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New quasi-Newton methods via higher order tensor models.

Many researches attempt to improve the efficiency of the usual quasi-Newton (QN) methods by accelerating the performance of the algorithm without causing more storage demand. They aim to employ more available information from the function values and gradient to approximate the curvature of the objec...

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Main Authors: Biglari, Fahmeh, Abu Hassan, Malik, Leong, Wah June
Format: Article
Language:English
English
Published: Elsevier 2011
Online Access:http://psasir.upm.edu.my/id/eprint/24642/1/New%20quasi.pdf
http://psasir.upm.edu.my/id/eprint/24642/
http://www.elsevier.com/
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spelling my.upm.eprints.246422015-08-26T06:39:58Z http://psasir.upm.edu.my/id/eprint/24642/ New quasi-Newton methods via higher order tensor models. Biglari, Fahmeh Abu Hassan, Malik Leong, Wah June Many researches attempt to improve the efficiency of the usual quasi-Newton (QN) methods by accelerating the performance of the algorithm without causing more storage demand. They aim to employ more available information from the function values and gradient to approximate the curvature of the objective function. In this paper we derive a new QN method of this type using a fourth order tensor model and show that it is superior with respect to the prior modification of Wei et al. (2006) [4]. Convergence analysis gives the local convergence property of this method and numerical results show the advantage of the modified QN method. Elsevier 2011-02-15 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/24642/1/New%20quasi.pdf Biglari, Fahmeh and Abu Hassan, Malik and Leong, Wah June (2011) New quasi-Newton methods via higher order tensor models. Journal of Computational and Applied Mathematics, 235 (8). pp. 2412-2422. ISSN 0377-0427 http://www.elsevier.com/ 10.1016/j.cam.2010.10.041 English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description Many researches attempt to improve the efficiency of the usual quasi-Newton (QN) methods by accelerating the performance of the algorithm without causing more storage demand. They aim to employ more available information from the function values and gradient to approximate the curvature of the objective function. In this paper we derive a new QN method of this type using a fourth order tensor model and show that it is superior with respect to the prior modification of Wei et al. (2006) [4]. Convergence analysis gives the local convergence property of this method and numerical results show the advantage of the modified QN method.
format Article
author Biglari, Fahmeh
Abu Hassan, Malik
Leong, Wah June
spellingShingle Biglari, Fahmeh
Abu Hassan, Malik
Leong, Wah June
New quasi-Newton methods via higher order tensor models.
author_facet Biglari, Fahmeh
Abu Hassan, Malik
Leong, Wah June
author_sort Biglari, Fahmeh
title New quasi-Newton methods via higher order tensor models.
title_short New quasi-Newton methods via higher order tensor models.
title_full New quasi-Newton methods via higher order tensor models.
title_fullStr New quasi-Newton methods via higher order tensor models.
title_full_unstemmed New quasi-Newton methods via higher order tensor models.
title_sort new quasi-newton methods via higher order tensor models.
publisher Elsevier
publishDate 2011
url http://psasir.upm.edu.my/id/eprint/24642/1/New%20quasi.pdf
http://psasir.upm.edu.my/id/eprint/24642/
http://www.elsevier.com/
_version_ 1643828422394249216
score 13.251813

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